issue_comments

Table actions

1 row where author_association = "MEMBER" and issue = 561539035 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date)

user 1

issue 1

  • to_dataframe fails if dataarray has dimension 1 · 1 ✖

author_association 1

  • MEMBER · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
583484851 https://github.com/pydata/xarray/issues/3761#issuecomment-583484851 https://api.github.com/repos/pydata/xarray/issues/3761 MDEyOklzc3VlQ29tbWVudDU4MzQ4NDg1MQ== dcherian 2448579 2020-02-07T16:29:43Z 2020-02-07T16:29:43Z MEMBER

So da.sel(x=[1],y=[1]).to_dataframe(name='test') works; this preserves the dimension. In your example, you're getting a scalar. I'm not sure if we should support this or raise a nicer error message.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   to_dataframe fails if dataarray has dimension 1 561539035

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

CREATE TABLE [issue_comments] (
   [html_url] TEXT,
   [issue_url] TEXT,
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [created_at] TEXT,
   [updated_at] TEXT,
   [author_association] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [issue] INTEGER REFERENCES [issues]([id])
);
CREATE INDEX [idx_issue_comments_issue]
    ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
    ON [issue_comments] ([user]);